Evidence of the effect of summertime midlatitude convection on the subtropical lower stratosphere from CRYSTAL‐FACE tracer measurements
Bibliographic record
Abstract
Trace gas and particle measurements taken during the CRYSTAL‐FACE mission are used to examine mixing in the summer subtropical lower stratosphere. Vigorous convection in the central and eastern United States injected a significant amount of tropospheric air into the lower stratosphere, which was subsequently advected over the region sampled during the CRYSTAL‐FACE mission. Aerosols produced by biomass burning were observed over Florida during a time period with a large number of forest fires in the western United States and eastern Canada, providing evidence of convective injection of tropospheric air into the lower stratosphere. The circumstances of the large‐scale flow pattern in the upper troposphere and lower stratosphere, vigorous summertime convection, abundant forest fires, and the downstream sampling allow a unique view of mixing in the lower stratosphere. We calculate the fractions of midlatitude tropospheric air in the sampled lower stratosphere and mixing rates on the basis of consistency between a number of tracer‐tracer correlations. The tropospheric endpoints to the mixing estimates give an indication of midlatitude continental convective input into the lower stratosphere. We also discuss the possible impact of summertime midlatitude convection on the composition of the stratosphere as a whole.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".